menu
Kaizenshogun77
Thesis Work in 10 weeks Star this Commitment
Week 8 of 10

Kaizenshogun77 commits to:
Submit 1500 words per week
6
1
Details
Last reported: Pending
Successful (pending referee feedback)
Next report due:
June 23
4:00 AM GMT
My Commitment Journal
Kaizenshogun77
Kaizenshogun77
June 23, 2021, 4:04 PM
I am running distribution and reliability test on my data in SPSS for Data Analysis
Kaizenshogun77
Kaizenshogun77
June 11, 2021, 10:37 AM
1.1 Background
There is an urgent need to transition towards an environmentally sustainable model of development globally (Goodland et al., 1993) that can preserve the Earth’s limited natural resources (Steffen et al., 2015). Human activities are destabilizing the Earth’s biosphere and are accelerating an upcoming and irreversible set of ‘planetary scale tipping points’ (Barnosky et al., 2012). Specifically, agricultural production plays an important role in rapidly pushing our planet towards these tipping points (Campbell et al., 2017). For example, food systems, from farm-to-fork, produce around 30% of total anthropogenic greenhouse gas (GHG) emissions ( Vermeulen et al., 2012; Garnett et al. 2015).
Beyond production, the supply chains of food systems have social, environmental and economic effects that prevent the achievement of sustainable development goals set up by the United Nations (Dania et al., 2018). A steady rise in the demand for food, and especially the demand of animal products, are caused respectively by a growing population (Davies et al., 2009) and an increase in global wealth (Campbell et al., 2017; Godfray et al., 2010). Such a rise in demands is contributing to the unsustainable impact our food system. The Food and Agriculture Organization of the United Nations has therefore determined that individual diet composition is a significant factor in decreasing the negative effects of food system (as cited in Heller et al. 2018); however so far, government regulations have been found inadequate and inefficient at managing the negatives externalities created by food systems (Thompson et al., 2007; Steier, 2011)).
More so than business practices, policies and regulations, the unsustainability of our food consumption can be attributed to consumer values and habits (Reisch et al., 2013). Despite consumer’ alimentation habits being manipulated by misrepresentation, addictive ingredients and advertising campaigns (Steier, 2011), consumers have the power to minimize the negative effects of existing food systems by purchasing lower impact foods (Joshi and Rahman, 2015; Redman and Redman, 2014). Therefore, changing people’s current eating habits to adopt diets with low environmental impact has become more crucial than ever (Heller et al., 2018; Hartmann and Siegrist., 2017; Magrini et al., 2018; Hedin et al., 2019). Unfortunately, deeply rooted food habits are difficult to change because they are the result of many complex factors interacting with each other (Aranceta et al., 2003), including social, economic, psychological, and environmental factors (Bublitz et al., 2010; Pollard et al., 2002; Renner et al., 2012).
Educating for conscious consumerism is a critical part of creating changes in production, consumption, and disposal systems (Redman & Redman, 2014). However, past educational (Arlinghaus and Johnston, 2017) and environmental programs have not been sufficient in creating behavior change because there is a gap between an individual’s thinking and their actions (Kollmuss and Agyeman 2002; Padel and Foster, 2005). It has been suggested that sustainability education must move beyond delivering information and become more grounded in behavior change theories in order to understand what truly motivates and constrains sustainable actions (Redman and Larson, 2011; Redman, 2013; Kaiser et al., 2003). Already, several studies have used theories of behavior change to effectively predict and understand the sustainable food attitude behavior gap (Vermeir and Verbeke 2006; Redman and Redman, 2014). Even though theories are useful in helping predict and modifying sustainable behaviors, they need to consider the specific context and type of sustainable behavior that is being targeted to inform the attitude behavior gap (Maki and Rothman, 2017). Furthermore, successful behavior change for sustainability needs to identify the persons within the population that are most receptive to change and target them with tailored behavior changes tools (e.g. Feedback, Goal setting, Nudge, persuasive technologies such as smartphone application and games) (Klaniecki et al., 2018), based on the behavior type, behavioral setting (Maki and Rothman, 2017) and the type of person (Abrahamse et al., 2007) being targeted for such change (Klaniecki et al., 2018).
Gamification “the use of game design elements in non-game context” (Deterding et al, 2011) is a behavior change concept that has shown great potential in promoting nutritional behaviors (Chow et al., 2020; Ezezika et al., 2018; Yoshida et al., 2020; Jones et al., 2014), health behaviors (King et al., 2013; Edwards et al., 2018), and various environmentally friendly behaviors (Ro et al., 2017; Kronisch, 2019), including sustainable food purchasing (Lounis et al., 2013; Berger, 2019). A review of gamification interventions demonstrated that the success rate of gamified interventions is immensely dependent on the context being gamified, and on the user type (Hamari et al., 2014). Because an intervention application that can adapt to the user-specific situation (e.g. social and environmental context) can improve the effectiveness of the digital intervention (Sucala et al., 2019), the design of a gamified intervention promoting and facilitating sustainable food procurement should be based on a segmentation and in-depth analysis of its potential users within the context of sustainable food purchasing. More recently, after experimenting with social norm-based feedback in a gamified online shopping environment, Berger (2019) stated that future studies investigating how to promote sustainable food purchase should consider “elaborate, phase specific, target group specific gamification interventions”. Since interviews with participants demonstrated that people react very differently to the same aspects of gamification within the same gamified shopping context aimed at promoting eco-friendly purchases (Lounis et al., 2013), a user segmentation is relevant in the context of sustainable food purchasing.

1.2 Research approach and goals
The purpose of this study is to provide an answer to the question: What are the: demographic, psychological and behavioural characteristics of consumers interested in purchasing sustainable foods and how can those characteristics be used to inform the design of targeted gamified interventions that would promote, facilitate, and maintain sustainable food purchasing?
To study the demographic, psychological, and behavioural characteristics of consumers interested in purchasing sustainable foods, an online survey was developed. First, the Theory of Planned Behavior (TPB; Ajzen 1985) was used to understand the target users’ motivations, challenges, and goals regarding the purchase of different types of sustainable food (e.g. local foods, organic foods, plant-based proteins); this is the most commonly used theory in behavior change interventions of sustainable behaviors (Klaniecki et al., 2018) as well as being one of the chief theory of behavior change that can reliably measure consumer intentions and behaviors in numerous contexts surrounding food choice (Nardi et al., 2019). Moreover, because findings have shown the importance of taking product category differences into account in studying consumer food motivations and intentions (Verain et al., 2017) the survey addressed different definitions and understandings of what are sustainable foods.
Secondly, to inform how those characteristics could be used to inform the design of targeted gamified interventions that would promote, facilitate, and maintain sustainable food purchasing, the TPB was used in conjunction with Marczewski’s (2015) Gamification User Types Hexad Scale (GUTHS). The Hexad scale is a gamification framework that analyzes the target users’ player type and was empirically validated (Tondello et al. 2016; Akgün and Topal, 2018). It was designed to match each user’s personality to specific game elements, for the purpose of tailoring personalized behavior change application (Mora et al. 2017); Zhao et al., 2020). The Hexad scale is grounded in a combination of Bartle’s player type framework (Bartle, 1996) and the Theory of Self-Determination (TSD) (Deci and Ryan, 2012). The resulting ‘Hexad player type scale’(HPTS) was found to be correlated to the Big 5 personality traits (Tondello et al. 2016), indicating the user’s preferences towards different game design elements guidelines (Orji et al., 2013).
Finally, the survey established each participant’s preferred medium as well as their previous behavior towards different genres of games. In conclusion, because gamification studies should “ focus on the relationships between game dynamics, gamification contexts, gaming personalities or preferences, dynamic gaming engagement styles etc.” (Tu et al., 2015), this research measured the demographic information of the participants as well as their motivations, challenges, and goals regarding the purchase of different types of sustainable food (e.g. local foods, organic foods, plant-based proteins), their player types, their past gaming behavior based on game genres, as well as their preferred smartphone application type that can be used as a medium ( i.e. behavior change tool) to implement gamified interventions.
The specific objectives of this study are: 1) to segment consumers based on their level of intention to buy sustainable foods (e.g. low-, medium- and high- intent to buy sustainable foods); and 2) to analyze the characteristics of the target consumers in order to adapt the gamification design of interventions that would effectively promote, facilitate, and maintain sustainable food purchasing.

1.3 Thesis Contributions
There is an urgent need to shift food consumption patterns to those that are more sustainable for human and environmental health, but it is extremely difficult to change human food consumption behaviors. Gamified interventions hold promise for behaviour change, but previous studies have found that the gamification design must be adapted to the specific characteristics of both the context targeted as well as the people that would use the gamified intervention.This study will contribute to furthering previous research investigating how gamification can efficiently promote sustainable food purchases (Berger, 2019; Lounis et al, 2013). Specifically, this empirical study will provide new insights into what psychological variables determine the intention of an individual to purchase certain types of sustainable foods (and possibly other sustainable goods). Furthermore, this research advances the field of gamification research by investigating and identifying ways that gamification frameworks, such as the HEXAD Player type framework (Marczewski, 2015), could be implemented into specific contexts for targeting specific consumer groups. Moreover, this could lead into a better understanding of whether these frameworks are relevant in the context of sustainable food purchases. In practice, the results may also be of interest for designing and implementing food literacy programs more effectively. To the best of my knowledge, no previous research has ever segmented a population to inform the design of gamified interventions aimed at promoting sustainable food purchasing.
1.4 Thesis Structure
This thesis has the following structure. The second Chapter will cover all relevant background information within the existing literature regarding concepts such as sustainable production and consumption, the interventions aiming to alter multiple behaviors concerning the areas of food, health, and environmental behaviors, as well as gamification interventions. The third Chapter will cover the methodology of the survey of over 400 participants living in Ontario, Canada in March 2021. Then, Chapter four discuss the results and their implications and limitations. Finally, Chapter five will make recommendations and concluding observations for future research for academics, practitioners, and policy makers.
Kaizenshogun77
Kaizenshogun77
May 26, 2021, 4:15 PM
Methodology
Study design
To study the demographic, psychological, and behavioural characteristics of consumers interested in purchasing sustainable foods an online survey was developed. The survey takes on average 18 minutes to complete. Questions from the survey were crafted based on two model of behavior change frameworks. First, the Theory of Planned Behavior (TPB; Ajzen 1985) will be used to understand the target users’ motivations, challenges, and goals regarding the purchase of different types of sustainable food (e.g. local foods, organic foods, plant-based proteins) since findings have shown the importance of taking product category differences into account in studying consumer food motivations and intentions (Verain et al., 2017).

The TPB has been extensively and effectively employed as the predominant model for the understanding, prediction and change of numerous human behaviors over the past decades (Sniehotta et al. 2014; Steinmetz et al., 2016). The theory of planned behavior is established as the most commonly used theory in behavior change interventions of sustainable behaviors (Klaniecki et al., 2018) as well as being one of the chief theory of behavior change that can reliably measure consumer intentions and behaviors in numerous contexts surrounding food choice (Nardi et al., 2019). For example, several adaptations of this model have been tailored to study healthy eating (Conner et al., 2002), environmental behaviors (Gkargkavouzi et al., 2019), organic food consomption (Donahue, 2017; Bagher et al., 2018) and buying environmentally sustainable products (Kumar, 2012). The TPB states that the main predictor of behavior is the intention to execute the behavior (Ajzen 1985, 1991, 2012). The TPB also suggests that the stronger the intention to perform a behavior, the more likely the behavior will actually occur (Ajzen, 2020). The TPB also clarifies that the strength of the intention depends on three variables: attitude towards the behavior, subjective norms, and perceived behavioral control (Ajzen 1991, 2012). In the survey, 55 Likert type items (i.e. 1= Strongly Disagree, 5= Strongly Agree; Likert 1= Never, and 5 =Always) measure the intention to purchase sustainable foods, as well as its motivations and barriers. Those questions were based on questionnaires from multiple studies using adapted versions of the TPB to measure the personal determinants of organic food consumption (Aertsens et al., 2009; Wang et al., 2019; Al-Swidi et al., 2014). The participant’s understanding of which type of aliment constitutes the most sustainable food (e.g. local foods, organic foods, plant-based proteins) was measured using 3 items that were ranked from 1 to 3 by the participant. Since the TPB has been successfully applied to studies investigating dietary and sustainable food consumption in the past, it is deemed a suitable model for the study of consumer purchase intentions towards sustainable foods.

Secondly, to inform how those characteristics could be used to inform the design of targeted gamified interventions that would promote, facilitate, and maintain sustainable food purchasing, the TPB will be used in conjunction with Marczewski’s (2015) Gamification User Types Hexad Scale (GUTHS). The Hexad scale is a gamification framework that analyzes the target users’ player type and was empirically validated (Tondello et al. 2016; Akgün and Topal, 2018). It was designed to match each user’s personality to specific game elements, for the purpose of tailoring personalized behavior change application (Mora et al. 2017); Zhao et al., 2020). The Hexad scale is grounded in a combination of Bartle’s player type framework (Bartle, 1996) and the Theory of Self-Determination (TSD) (Deci and Ryan, 2012). The SDT addresses both intrinsic and extrinsic motives for action (Berger & Schrader, 2016). According to Ryan & Deci (2000), intrinsic motivation, refers to doing something because it is inherently interesting or enjoyable, and extrinsic motivation, refers to doing something because it leads to a separable outcome. The SDT theory is based on three psychological needs: autonomy, competence and relatedness, which can be addressed by gamified interventions contributing to enjoyment, regardless of the specific content, complexity, or genre of games (Przybylski et al., 2010). The resulting ‘Hexad player type scale’(HPTS) was found to be correlated to the Big 5 personality traits (Tondello et al. 2016), indicating the user’s preferences towards different game design elements guidelines (Orji et al., 2013). The HPTS is measured in this study using 18 Likert type items ( i.e. 1= Strongly Disagree, and 5= Strongly agree). This information will inform practitioners and academics on how to implement game elements based on the characteristics and preferences of the target users.

Finally, 12 ranked items ( i.e. ranked from 1 to 12) will established each participant’s preferred medium in this survey, and 5 items (i.e. Likert 1= Never, and 5 =Always) measure previous behavior towards different types of games. Attitude towards gamified systems have to be considered when investigating the effect of gamification on behavior change (Berger…). It was demonstrated that different user characteristics determine the attitude they each have towards gamification, thus explaining why in certain environment or only with certain users, gamification has significant effects (Hamari et al., 2014). For example, it was found that using gamification with a smart phone, (i.e. fantasy and challenge), was effective to improve customer retailing experience (Poncin et al. 2017). Moreover, people who have a passion for gaming or individuals who grew up with the internet, the use of smartphones and social media (i.e., digital natives) will probably respond differently to gamified interventions using different behavior change tools and mediums than digital immigrants who were not born learning the digital language of computers, video games and the Internet (Prenzy, 2001).
Consequently, to investigate the effectiveness of gamification in a context as realistic as possible, we have to figure out the best medium or tool (e.g. website, application for smartphone) for implementing gamification based on the context and type of behavior targeted (Klaniecki et al., 2018). Because gamification studies should “ focus on the relationships between game dynamics, gamification contexts, gaming personalities or preferences, dynamic gaming engagement styles etc” (Tu et al., 2015), the online survey will measure the demographic information of the participants as well as their motivations, challenges, and goals regarding the purchase of different types of sustainable food (e.g. local foods, organic foods, plant-based proteins), their player types, and their past gaming behavior based on game genre as well as their preferred smartphone application type that can be used as a medium for gamified interventions.

Sampling and data collection
Several sample size calculators suggested between 383 and 400 participants when provided with a margin of error at a confidence level of 95% for a population of 100,000 people. I chose this level of confidence because it is the most widely used in research (Finch and Cumming, 2009). I selected a population size of 100,000 people because the sample size does not change much once it becomes larger than 50,000 people. The mathematics of probability shows that the size of the population is irrelevant, unless the size of the sample exceeds a few percent of the total population examined. This means that a sample of 400 people is equally useful in examining the opinions of a province of 15,000,000 as it would a city of 100,000. For instance, Qualtrics sample calculator suggests 383 participants. Creative Research System calculator as well as Checkmarket calculator also suggest 383 participants. SurveyMonkey calculator suggests that 400 participants should be used when provided with the same variables (i.e. a margin of error at a confidence level of 95% and a population of 100,000 people). Thus, I expect 400 participants to take part in this study.


The survey was designed and administered online through the Qualtrics survey software in both French and English and was then distributed through a panel participants recruitement company named ‘Quest mindshare’. The data was collected in the month of March 2020.
The student investigator paid Quest Mindshare for their service of providing adequate participants to the study based on quotas regarding Gender, Income, and age. Those quotas were implemented within the data collection process to ensure that the participants were representative of Ontario population distribution based on 2019 census of Canada. The participation in the study was voluntary, anonymous, and rewarded with a financial incentive provided by Quest MindShare to the respondents. The study received ethics approval from the University of Waterloo, Ontario.

Hypotheses and objectives

Specific objectives are to:
A. Identify how the target market defines a sustainable diet.

B. Identify the demographic characteristics of the target market.

C. Determine which personal variables (e.g. attitudes, behavioral control, social norm, personal moral norm, emotions) are associated with the intent to purchase sustainable food.

D. Identify the barriers and drivers associated with those who have a high level of intent to purchase sustainable food.

E. Identify the factors (i.e. player types, game playing habits, preferred mobile application types) required for the design of a gamified intervention which would aim to promote, facilitate and maintain the sustainable food purchase of users who have a high level of intent to purchase sustainable food

Hypothesis 1: Gender, education and income are related to the intent to purchase sustainable food.

Hypothesis 2: There is a relationship between the personal variables (i.e. attitudes, behavioral control, social norm, personal moral norm, emotions) and the intent to purchase sustainable food.


Statistical Tool

(…Will be completed next time)

Statistical Analysis

sparc
sparc
May 26, 2021, 8:43 AM
Hey Kaizenshogun77, your thesis progress is inspirational as I'm also writing my masters' thesis. I'd like to say, you're doing great... just kill it!!
    This Commitment has no photos.
Displaying 1-4 of 7 results.
June 16 to June 23
Successful (pending referee feedback)
Success
Pending
June 9 to June 16
Successful
Success
Success

mitzuyley
mitzuyley
- Referee approval report
Kaizenshogun77
Kaizenshogun77
- Committed user success report
June 2 to June 9
Successful (referee feedback expired)
Success
No report submitted
May 26 to June 2
Not Successful
No report submitted
No report submitted
Recipient of Stakes
Money to a friend ($10.00 to mitzuyley per failed reporting period)
To change the Recipient of Stakes for your Thesis Work in 10 weeks Commitment, enter their email address or stickK username below.
Total at stake: $100.00
Stakes per period: $10.00
Remaining Stakes: $30.00
Total Money Lost: $10.00
Referee
Supporters
.
Your feedback has been sent. Thank you!
This website uses cookies to ensure you get the best experience on our website. Read our Privacy Policy